Hemagglutinin Sequences Research Articles

Sequence and Phylogenetic Analysis of Influenza Virus (H1N1pdm2009) Circulating in Riyadh, Saudi Arabia

Influenza A virus (IAV) is the principal cause of seasonal flu and is often reported among pilgrims in Saudi Arabia (SA) due to their mass gatherings. The epidemiological, phylogenetic, and molecular details of A/H1N1pdm2009 in 200 clinical samples collected from hospitalized children in Riyadh during two epidemic seasons (2020/21 and 2021/22) are reported in this study. A total of 21 (10.50%) samples were positive for IAV, as determined using PCR. Fifteen isolates (71.42%) were identified as H1N1pdm2009: eight (53.33%) samples were from males, seven (46.67%) from females. The prevalence of H1N1pdm2009 isolates was significantly (p < 0.05) higher among the age group 15-64 years than the other age groups. A comparison of hemagglutinin (HA) and neuraminidase (NA) amino acid sequences between SA H1N1pdm and certain vaccine strains revealed 19 mutations relative to reference strain A/California/07/2009. Among them, eight (0.47%) were in HA, and eight (0.56%) were in NA sequences that differed from vaccine strains. All isolates of the 2020–2022 seasons exhibited N- and O-glycosylation sites comparable to vaccine strains. Phylogenetically their HA and NA genes are divided into different clades. Most of the studied isolates (five) belonged to clade 5a.1 of HA. These data identify the genetic makeup of circulating influenza virus subtypes.

Enhancement of protective efficacy of recombinant attenuated Salmonella typhimurium delivering H9N2 avian influenza virus hemagglutinins(HA) antigen vaccine candidate strains by C-C motif chemokine ligand 5 in chickens(chCCL5)

The H9N2 inactivated avian influenza vaccine cannot induce cellular and mucosal immune responses, while the attenuated Salmonella vector as an intracellular bacterium can induce dominant cellular and mucosal immune responses. However, it provides low protection against the virus when delivering viral antigens and needs further optimization. Chicken C-C motif chemokine ligand 5 (chCCL5) is an important CC chemokine associated with immune cell chemotaxis, migration, and viral infection. This study connected the sequence of chCCL5 (CCL5) with the hemagglutinin sequence of the H9N2 avian influenza virus (yH9HA), utilizing the attenuated Salmonella typhimurium vector containing the delayed lysis system MazE/F regulated by arabinose as a carrier. A vaccine strain of recombinant attenuated Salmonella typhimurium and H9N2 avian influenza virus HA, rSC0130 (pS0017-yH9HA-CCL5), was successfully constructed. The experimental results indicate that yH9HA-CCL5 can be expressed in 293 T cells; compared to the strain without CCL5, rSC0130 (pS0017-yH9HA-CCL5) can induce significantly increased cellular immune responses and provide better protective effects in H9N2 virus challenge experiments. The above results indicate that chCCL5 can significantly enhance the protective effect of Salmonella delivering H9N2 avian influenza virus HA protein vaccine against H9N2 avian influenza virus infection, providing valuable theoretical support for further improving the protective efficiency of recombinant attenuated Salmonella vectors for delivering viral antigens.

Evolution of Influenza A(H3N2) Viruses in Bhutan for Two Consecutive Years, 2022 and 2023.

Influenza A viruses pose a significant public health threat globally and are characterized by rapid evolution of the hemagglutinin (HA) gene causing seasonal epidemics. The aim of this study was to investigate the evolutionary dynamics of A(H3N2) circulating in Bhutan during 2022 and 2023. We analysed 166 whole-genome sequences of influenza A(H3N2) from Bhutan, obtained from the GISAID database. We employed a Bayesian Markov Chain Monte Carlo (MCMC) framework, with a curated global dataset of HA sequences from regions with significant migration links to Bhutan. Phylogenetic, temporal, and phylogeographic analyses were conducted to elucidate the evolutionary dynamics and spatial dissemination of the viruses. Our phylogenetic analysis identified the circulation of influenza A(H3N2) Clade 3C.2a1b.2a.2 in Bhutan during 2022 and 2023, with viruses further classified into three subclades: 2a.3 (39/166), 2a.3a.1 (58/166) and 2a.3b (69/166). The TMRCA estimates suggest that these viral lineages originated approximately 1.93 years prior to their detection. Phylogeographic analysis indicates introductions from the United States in 2022 and Australia in 2023. The mean evolutionary rate across all gene segments was calculated to be 4.42 × 10-3 substitutions per site per year (95% HPD: 3.19 × 10-3 to 5.84 × 10-3), with evidence of purifying selection and limited genetic diversity. Furthermore, reassortment events were rare, with an estimated rate of 0.045 events per lineage per year. Our findings show that primary forces shaping the local evolution of the influenza A(H3N2) in Bhutan are largely stochastic, with only sporadic instances of adaptive change, and thus underscore the importance of continuous surveillance to mitigate the impact of evolving strains.

Efficacy of the H7N9 vaccine as a candidate for the Korean avian influenza antigen bank

The avian influenza A virus (H7N9), first detected in China in 2013, is a zoonotic virus that remains persistent in bird populations despite a decline in human cases owing to control measures. Therefore, this study aimed to develop a vaccine as one preventive strategy in anticipation of the potential entry of H7N9 into Korea. Using the hemagglutinin and neuraminidase consensus sequences of H7N9 from 2018–2019, a recombinant H7N9 vaccine, rgAPQAH7N9, was developed, and its protective efficacy in specific pathogen-free chickens was evaluated. The rgAPQAH7N9 vaccine exhibited proliferation in eggs and demonstrated high immunogenicity, with a hemagglutination inhibition titer of 9.3 log2. Furthermore, the vaccine provided complete protection, as vaccinated chickens did not exhibit clinical signs or viral shedding. Moreover, when the rgAPQAH7N9 vaccine was boosted, the resulting immunity was long-lasting, with hemagglutination inhibition titers > 7 log2 persisting after 6 months. Therefore, the rgAPQAH7N9 vaccine virus may be considered a potential candidate for inclusion in the avian influenza antigen bank to ensure preparedness for emergency vaccination in poultry.

Utilizing machine learning and hemagglutinin sequences to identify likely hosts of influenza H3Nx viruses

Influenza is a disease that represents both a public health and agricultural risk with pandemic potential. Among the subtypes of influenza A virus, H3 influenza virus can infect many avian and mammalian species and is therefore a virus of interest to human and veterinary public health. The primary goal of this study was to train and validate classifiers for the identification of the most likely host species using the hemagglutinin gene segment of H3 viruses. A five-step process was implemented, which included training four machine learning classifiers, testing the classifiers on the validation dataset, and further exploration of the best-performing model on three additional datasets. The gradient boosting machine classifier showed the highest host-classification accuracy with a 98.0 % (95 % CI [97.01, 98.73]) correct classification rate on an independent validation dataset. The classifications were further analyzed using the predicted probability score which highlighted sequences of particular interest. These sequences were both correctly and incorrectly classified sequences that showed considerable predicted probability for multiple hosts. This showed the potential of using these classifiers for rapid sequence classification and highlighting sequences of interest. Additionally, the classifiers were tested on a separate swine dataset composed of H3N2 sequences from 1998 to 2003 from the United States of America, and a separate canine dataset composed of canine H3N2 sequences of avian origin. These two datasets were utilized to look at the applications of predicted probability and host convergence over time. Lastly, the classifiers were used on an independent dataset of environmental sequences to explore the host identification of environmental sequences. The results of these classifiers show the potential for machine learning to be used as a host identification technique for viruses of unknown origin on a species-specific level.

Codon optimized influenza H1 HA sequence but not CTLA-4 targeting of HA antigen to enhance the efficacy of DNA vaccines in an animal model

Infections caused by the influenza virus lead to both epidemic and pandemic outbreaks in humans and animals. Owing to their rapid production, safety, and stability, DNA vaccines represent a promising avenue for eliciting immunity and thwarting viral infections. While DNA vaccines have demonstrated substantial efficacy in murine models, their effectiveness in larger animals remains subdued. This limitation may be addressed by augmenting the immunogenicity of DNA-based vaccines. In the investigation here, protein expression was enhanced via codon optimization and then mouse cytotoxic T-lymphocyte antigen 4 (CTLA-4) was harnessed as a modulatory adjunct to bind directly to antigen-presenting cells. Further, the study evaluated the immunogenicity of two variants of the hemagglutinin (HA) antigen, i.e. the full-length and the C-terminal deletion versions. The study findings revealed that the codon-optimized HA gene (pcHA) led to increased protein synthesis, as evidenced by elevated mRNA levels. Codon optimization also significantly bolstered both cellular and humoral immune responses. In cytokine assays, all plasmid constructs, particularly pCTLA4-cHA, induced robust interferon (IFN)-γ production, while interleukin (IL)-4 levels remained uniformly non-significant. Mice immunized with pcHA displayed an augmented presence of IFNγ+ T-cells, underscoring the enhanced potency of the codon-optimized HA vaccine. Contrarily, CTLA-4-fused DNA vaccines did not significantly amplify the immune response.

Genetic characteristics of influenza A and B viruses circulating in Russia in 2019-2023.

Relevance. Influenza viruses have a high potential for genetic change. These viruses are monitored annually around the world, including Russia, to determine the dominant genetic groups and select the strains to be included in influenza vaccines. Aims of the study include: analysis of the circulation of influenza viruses in Russia in 2019-2023, phylogenetic and molecular analysis of hemagglutinin (HA) sequences of influenza virus strains, detection of drug resistance mutations to neuraminidase (NA) inhibitors and M2-protein (M2) ion channel inhibitors. Materials and methods. Biological samples containing RNA of influenza viruses were studied: 417 A(H1N1)pdm09, 147 A(H3N2) and 167 B(Victoria). Sequencing of the PCR fragments was performed on the 3500xL Genetic Analyzer (Applied Biosytems). Data processing and analysis were carried out using DNASTAR, Nextclade, FluSurver and BioNumerics v.6.6 software. Results. Influenza A(H1N1)pdm09, A(H3N2), B(Victoria) viruses circulating in 2019-2023 were investigated. The highest variability of HA was observed in A(H3N2) viruses. 3% of A(H1N1)pdm09 viruses had the D222N mutation in the receptor-binding site of HA, which is associated with more severe disease. The oseltamivir and zanamivir resistance mutation H275Y in NA was detected in 2% of influenza A(H1N1)pdm09 viruses. No oseltamivir and zanamivir resistance mutations in NA were detected in all influenza A(H3N2) and B viruses tested. In all investigated influenza A(H1N1)pdm09 and A(H3N2) viruses the adamantane resistance mutation S31N in M2 was identified. Conclusions. The detection of amino acid substitutions in HA antigenic sites and resistance mutations in NA and M2 confirms the evolution of influenza viruses and the need for continuous genetic surveillance.

Recent Occurrence, Diversity, and Candidate Vaccine Virus Selection for Pandemic H5N1: Alert Is in the Air.

The prevalence of the highly pathogenic avian influenza virus H5N1 in wild birds that migrate all over the world has resulted in the dissemination of this virus across Asia, Europe, Africa, North and South America, the Arctic continent, and Antarctica. So far, H5N1 clade 2.3.4.4.b has reached an almost global distribution, with the exception of Australia and New Zealand for autochthonous cases. H5N1 clade 2.3.4.4.b, derived from the broad-host-range A/Goose/Guangdong/1/96 (H5N1) lineage, has evolved, adapted, and spread to species other than birds, with potential mammal-to-mammal transmission. Many public health agencies consider H5N1 influenza a real pandemic threat. In this sense, we analyzed H5N1 hemagglutinin sequences from recent outbreaks in animals, clinical samples, antigenic prototypes of candidate vaccine viruses, and licensed human vaccines for H5N1 with the aim of shedding light on the development of an H5N1 vaccine suitable for a pandemic response, should one occur in the near future.

A Rationally Designed H5 Hemagglutinin Subunit Vaccine Provides Broad-Spectrum Protection against Various H5Nx Highly Pathogenic Avian Influenza Viruses in Chickens.

The evolution of the H5 highly pathogenic avian influenza (HPAI) viruses has led to the emergence of distinct groups with genetically similar clusters of hemagglutinin (HA) sequences. In this study, a consensus H5 HA sequence was cloned into the baculovirus expression system. The HA protein was expressed in baculovirus-infected insect cells and utilized as the antigen for the production of an oil emulsion-based H5 avian influenza vaccine (rBacH5Con5Mut). Twenty-one-day-old SPF chickens were immunized with this vaccine and then challenged at 21 days post-vaccination with clade 2.3.2.1, clade 2.3.4.4, and clade 7.2 of H5 HPAI viruses. The sera of vaccinated chickens exhibited high hemagglutination inhibition (HI) titers against the rBacH5 vaccine antigen, while lower HI titers were observed against the different challenge virus H5 hemagglutinins. Furthermore, the rBacH5Con5Mut vaccine provided 100% protection from mortality and clinical signs. Virus isolation results showed that oropharyngeal and cloacal shedding was prevented in 100% of the vaccinated chickens when challenged with clade 2.3.2.1 and clade 2.3.4.4 H5 viruses. When the rBacH5Con5Mut vaccine candidate was administrated at one day of age, 100% protection was demonstrated against the challenge of clade 2.3.4.4 virus at three weeks of age, indicating the potential of this vaccine for hatchery vaccination. Overall, A single immunization of rBacH5Con5Mut vaccine candidate with a consensus HA antigen can protect chickens against different clades of H5 HPAI viruses throughout the rearing period of broiler chickens without a boost, thus fulfilling the criteria for an efficacious broad-spectrum H5 avian influenza vaccine.

Proposal for a Global Classification and Nomenclature System for A/H9 Influenza Viruses.

Influenza A/H9 viruses circulate worldwide in wild and domestic avian species, continuing to evolve and posing a zoonotic risk. A substantial increase in human infections with A/H9N2 subtype avian influenza viruses (AIVs) and the emergence of novel reassortants carrying A/H9N2-origin internal genes has occurred in recent years. Different names have been used to describe the circulating and emerging A/H9 lineages. To address this issue, an international group of experts from animal and public health laboratories, endorsed by the WOAH/FAO Network of Expertise on Animal Influenza, has created a practical lineage classification and nomenclature system based on the analysis of 10,638 hemagglutinin sequences from A/H9 AIVs sampled worldwide. This system incorporates phylogenetic relationships and epidemiologic characteristics designed to trace emerging and circulating lineages and clades. To aid in lineage and clade assignment, an online tool has been created. This proposed classification enables rapid comprehension of the global spread and evolution of A/H9 AIVs.

Genomic evolution of influenza during the 2023–2024 season, the johns hopkins health system

Influenza, a human disease caused by viruses in the Orthomyxoviridae family, is estimated to infect 5% –10 % of adults and 20% –30 % of children annually. Influenza A (IAV) and Influenza B (IBV) viruses accumulate amino acid substitutions (AAS) in the hemagglutinin (HA) and neuraminidase (NA) proteins seasonally. These changes, as well as the dominating viral subtypes, vary depending on geographical location, which may impact disease prevalence and the severity of the season. Genomic surveillance is crucial for capturing circulation patterns and characterizing AAS that may affect disease outcomes, vaccine efficacy, or antiviral drug activities. In this study, whole-genome sequencing of IAV and IBV was attempted on positive remnant clinical samples (587) collected from 580 patients between June 2023 and February 2024 in the Johns Hopkins Health System (JHHS). Full-length HA segments were obtained from 424 (72.2 %) samples. H1N1pdm09 (71.7 %) was the predominant IAV subtype, followed by H3N2 (16.7 %) and IBV-Victoria clade V1A.3a.2 (11.6 %). Within H1N1pdm09 HA sequences, the 6B1A.5a.2a.1 (60.5 %) clade was the most represented. Full-length NA segments were obtained from 421 (71.7 %) samples. Within H1N1pdm09 and IBV, AAS previously proposed to change susceptibility to NA inhibitors were infrequently detected. Phylogeny of HA and NA demonstrated heterogeneous HA and NA H1N1pdm09 and IBV subclades. No significant differences were observed in admission rates or use of supplemental oxygen between different subtypes or clades. Influenza virus genomic surveillance is essential for understanding the seasonal evolution of influenza viruses and their association with disease prevalence and outcomes.

MetaFluAD: meta-learning for predicting antigenic distances among influenza viruses.

Influenza viruses rapidly evolve to evade previously acquired human immunity. Maintaining vaccine efficacy necessitates continuous monitoring of antigenic differences among strains. Traditional serological methods for assessing these differences are labor-intensive and time-consuming, highlighting the need for efficient computational approaches. This paper proposes MetaFluAD, a meta-learning-based method designed to predict quantitative antigenic distances among strains. This method models antigenic relationships between strains, represented by their hemagglutinin (HA) sequences, as a weighted attributed network. Employing a graph neural network (GNN)-based encoder combined with a robust meta-learning framework, MetaFluAD learns comprehensive strain representations within a unified space encompassing both antigenic and genetic features. Furthermore, the meta-learning framework enables knowledge transfer across different influenza subtypes, allowing MetaFluAD to achieve remarkable performance with limited data. MetaFluAD demonstrates excellent performance and overall robustness across various influenza subtypes, including A/H3N2, A/H1N1, A/H5N1, B/Victoria, and B/Yamagata. MetaFluAD synthesizes the strengths of GNN-based encoding and meta-learning to offer a promising approach for accurate antigenic distance prediction. Additionally, MetaFluAD can effectively identify dominant antigenic clusters within seasonal influenza viruses, aiding in the development of effective vaccines and efficient monitoring of viral evolution.

Unveiling the molecular epidemiology of canine distemper virus in Namibia: An expected pathogen showing an unexpected origin

ObjectiveCanine distemper virus (CDV) is a highly infectious virus that represents a threat for domestic dogs and several wild species. Despite recognized in several African countries, current knowledge of its molecular epidemiology is scarce and poorly updated. DesignTwenty-two hemagglutinin sequences, obtained from symptomatic Namibian dogs from 2020 to 2023, were analysed through phylogenetic and phylodynamic analysis to characterize the local CDV epidemiology and contextualize it in the international scenario. ResultsTwo unrelated clades were identified, including strains sampled in different Namibian towns, in the absence of a strong geographical clustering. The ancestors of the two clades were estimated to have originated from South America, likely Brazil, and South Africa, approximately in 2000 and 2006, respectively. While the introduction from South Africa was predictable, the introduction from Brazil was unexpected. The mediation of other African countries, particularly Angola, appears to be the most likely importation pathway. ConclusionsThe occurrence of multiple introduction events, likely originating from cross-border illegal animal trade between African countries, and the absence of any geographical clustering within Namibian regions, suggest a need for further investigation into its spreading pattern, as well as improved biosecurity measures to limit foreign viral introduction into the country.

The amino acid variation at hemagglutinin sites 145, 153, 164 and 200 modulate antigenicity andreplication of H9N2 avian influenza virus

H9N2 avian influenza virus (AIV), one of the predominant subtypes circulating in the poultry industry, inflicts substantial economic damage. Mutations in the hemagglutinin (HA) and neuraminidase (NA) proteins of H9N2 frequently alter viral antigenicity and replication. In this paper, we analyzed the HA genetic sequences and antigenic properties of 26 H9N2 isolates obtained from chickens in China between 2012 and 2019. The results showed that these H9N2 viruses all belonged to h9.4.2.5, and were divided into two clades. We assessed the impact of amino acid substitutions at HA sites 145, 149, 153, 164, 167, 168, and 200 on antigenicity, and found that a mutation at site 164 significantly modified antigenic characteristics. Amino acid variations at sites 145, 153, 164 and 200 affected virus's hemagglutination and the growth kinetics in mammalian cells. These results underscore the critical need for ongoing surveillance of the H9N2 virus and provide valuable insights for vaccine development.

Resurgence of influenza with increased genetic diversity of circulating viruses during the 2022-2023 season.

Introduction. After two seasons of absence and low circulation, influenza activity increased significantly in the winter of 2022-2023. This study aims to characterize virological and epidemiological aspects of influenza infection in Bulgaria during the 2022-2023 season and perform a phylogenetic/molecular analysis of the hemagglutinin (HA) and neuraminidase (NA) sequences of representative influenza strains.Hypothesis/Gap Statement. Influenza A and B viruses generate new genetic groups/clades each season, replacing previously circulating variants. This results in increased antigenic distances from current vaccine strains. Strengthening existing influenza surveillance is essential to meet the challenges posed by the co-circulation of influenza and SARS-CoV-2.Methodology. We tested 2713 clinical samples from patients with acute respiratory illnesses using a multiplex real-time RT-PCR kit (FluSC2) to detect influenza A/B and Severe acute respiratory syndrome coronavirus-2(SARS-CoV-2) simultaneously. Representative Bulgarian influenza strains were sequenced at the WHO Collaborating Centres in London, UK, and Atlanta, USA.Results. Influenza virus was detected in 694 (25.6 %) patients. Of these, 364 (52.4 %), 213 (30.7 %) and 117 (16.9 %) were positive for influenza A(H1N1)pdm09, A(H3N2) and B/Victoria lineage virus, respectively. HA genes of the 47 influenza A(H1N1)pdm09 viruses fell into clades 5a.2. and 5a.2a.1 within the 6B.5A.1A.5a.2 group. Twenty-seven A(H3N2) viruses belonging to subclades 2b, 2a.1, 2a.1b and 2a.3a.1 within the 3C.2a1b.2a.2 group were analysed. All 23 sequenced B/Victoria lineage viruses were classified into the V1A.3a.2 group. We identified amino acid substitutions in HA and NA compared with the vaccine strains, including several substitutions in the HA antigenic sites.Conclusion. The study's findings showed genetic diversity among the influenza A viruses and, to a lesser extent, among B viruses, circulating in the first season after the lifting of anti-COVID-19 measures.

H19 influenza A virus exhibits species-specific MHC class II receptor usage

Avian influenza A virus (IAV) surveillance in Northern California, USA, revealed unique IAV hemagglutinin (HA) genome sequences in cloacal swabs from lesser scaups. We found two closely related HA sequences in the same duck species in 2010 and 2013. Phylogenetic analyses suggest that both sequences belong to the recently discovered H19 subtype, which thus far has remained uncharacterized. We demonstrate that H19 does not bind the canonical IAV receptor sialic acid (Sia). Instead, H19 binds to the major histocompatibility complex class II (MHC class II), which facilitates viral entry. Unlike the broad MHC class II specificity of H17 and H18 from bat IAV, H19 exhibits a species-specific MHC class II usage that suggests a limited host range and zoonotic potential. Using cell lines overexpressing MHC class II, we rescued recombinant H19 IAV. We solved the H19 crystal structure and identified residues within the putative Sia receptor binding site (RBS) that impede Sia-dependent entry.

Structural basis for the broad antigenicity of the computationally optimized influenza hemagglutinin X6

Influenza causes significant morbidity and mortality. As an alternative approach to current seasonal vaccines, the computationally optimized broadly reactive antigen (COBRA) platform has been previously applied to hemagglutinin (HA). This approach integrates wild-type HA sequences into a single immunogen to expand the breadth of accessible antibody epitopes. Adding to previous studies of H1, H3, and H5 COBRA HAs, we define the structural features of another H1 subtype COBRA, X6, that incorporates HA sequences from before and after the 2009 H1N1 influenza pandemic. We determined structures of this antigen alone and in complex with COBRA-specific as well as broadly reactive and functional antibodies, analyzing its antigenicity. We found that X6 possesses features representing both historic and recent H1 HA strains, enabling binding to both head- and stem-reactive antibodies. Overall, these data confirm the integrity of broadly reactive antibody epitopes of X6 and contribute to design efforts for a next-generation vaccine.

Exploring the Function of Predicted T‐Cell Epitopes in Enhancing Influenza Virus Vaccine Efficacy

AbstractThis study investigates the potential utility of predicted T‐cell epitopes derived from the hemagglutinin (HA) sequences of the H1N1 and H5N1 serotypes of the influenza virus. The aim is to contribute to the improvement of a valuable influenza virus vaccine. The influenza virus, a member of the Orthomyxoviridae family, causes the contagious illness commonly known as the “flu.” It contains RNA and exhibits symptoms ranging from mild to severe, including fever, runny nose, sore throat, muscle aches, headaches, coughing, fatigue, and weakness. Each year, the flu epidemic results in a significant number of deaths and cases of severe illness worldwide. The study focuses on the HA protein, which is very useful for entry of virus and host cell strap, and the neuraminidase (NA) enzyme, which facilitates the free of the virus from the host cell. By utilizing computational tools such as Propred 1 and Propred, binding predictions for MHC class I and II are generated and conserved sequences are analyzed. The 3D structures of MHC class I and II human molecules are obtained from the Protein Data Bank (PDB) using the PATCH‐DOCK server. Through patch docking of the analyzed conserved sequences with MHC I and II human molecules, conserved epitopes that hold potential for vaccine development are identified. This research highlights the importance of utilizing predicted T‐cell epitopes in the design of effective influenza virus vaccines. By leveraging computational methods and structural analysis, this approach provides insights into the development of vaccines that target specific influenza virus serotypes. The identified conserved epitopes have the potential to enhance vaccine efficacy and contribute to the ongoing efforts to combat influenza virus infections.

PREDAC-CNN: predicting antigenic clusters of seasonal influenza A viruses with convolutional neural network.

Vaccination stands as the most effective and economical strategy for prevention and control of influenza. The primary target of neutralizing antibodies is the surface antigen hemagglutinin (HA). However, ongoing mutations in the HA sequence result in antigenic drift. The success of a vaccine is contingent on its antigenic congruence with circulating strains. Thus, predicting antigenic variants and deducing antigenic clusters of influenza viruses are pivotal for recommendation of vaccine strains. The antigenicity of influenza A viruses is determined by the interplay of amino acids in the HA1 sequence. In this study, we exploit the ability of convolutional neural networks (CNNs) to extract spatial feature representations in the convolutional layers, which can discern interactions between amino acid sites. We introduce PREDAC-CNN, a model designed to track antigenic evolution of seasonal influenza A viruses. Accessible at http://predac-cnn.cloudna.cn, PREDAC-CNN formulates a spatially oriented representation of the HA1 sequence, optimized for the convolutional framework. It effectively probes interactions among amino acid sites in the HA1 sequence. Also, PREDAC-CNN focuses exclusively on physicochemical attributes crucial for the antigenicity of influenza viruses, thereby eliminating unnecessary amino acid embeddings. Together, PREDAC-CNN is adept at capturing interactions of amino acid sites within the HA1 sequence and examining the collective impact of point mutations on antigenic variation. Through 5-fold cross-validation and retrospective testing, PREDAC-CNN has shown superior performance in predicting antigenic variants compared to its counterparts. Additionally, PREDAC-CNN has been instrumental in identifying predominant antigenic clusters for A/H3N2 (1968-2023) and A/H1N1 (1977-2023) viruses, significantly aiding in vaccine strain recommendation.

Phylogenetic identification of influenza virus candidates for seasonal vaccines.

The seasonal influenza (flu) vaccine is designed to protect against those influenza viruses predicted to circulate during the upcoming flu season, but identifying which viruses are likely to circulate is challenging. We use features from phylogenetic trees reconstructed from hemagglutinin (HA) and neuraminidase (NA) sequences, together with a support vector machine, to predict future circulation. We obtain accuracies of 0.75 to 0.89 (AUC 0.83 to 0.91) over 2016-2020. We explore ways to select potential candidates for a seasonal vaccine and find that the machine learning model has a moderate ability to select strains that are close to future populations. However, consensus sequences among the most recent 3 years also do well at this task. We identify similar candidate strains to those proposed by the World Health Organization, suggesting that this approach can help inform vaccine strain selection.